Mistry, Malcolm Noshir (2019): A High-Resolution (0.25 degree) Historical Global Gridded Dataset of Climate Extreme Indices (1970-2016) using GLDAS data. PANGAEA, https://doi.org/10.1594/PANGAEA.898014, Supplement to: Mistry, MN (2019): A high resolution global gridded historical dataset of climate extreme indices. Data, 4(1), https://doi.org/10.3390/data4010041
Always quote above citation when using data! You can download the citation in several formats below.
71 core and non-core climate extreme indices based on the Expert Team on Climate Change Detection and Indices (ETCCDI), and the Expert Team on Sector-specific Climate Indices (ET-SCI). The indices are computed using R ClimPACT2 package. The dataset does not include two indices (Heating and Cooling Degree Days) as these are computed separately for various baseline temperature (thresholds) -See 'A High-Resolution (0.25 degree) Daily Global Gridded Historical dataset of indices relevant for health and energy sector'-. All indices are computed using daily near-surface maximum and minimum temperature (deg C), and near-surface precipitation (mm/day) variables from Global Land Data Acquisation System (GLDAS) ver. 2 (@ 0.25 degree)
Data are in netCDF-4 format, at a spatial resolution of 0.25 degree by 0.25 degree (latitude by longitude)on a regular lon-lat grid. Some indices have data both at monthly and annual time-steps (as identified by the netCDF file name). Missing values are identified by values '1.e+20f'. Further details of the variables in the individual netCDF files can be checked using either NCO or CDO command line utilites as follows: "ncdump -h netcdf_file_name", "cdo sinfo netcdf_file_name".
The developement of this dataset has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 756194 (ENERGYA).
356 data points